2018 International Conference on Big Data Technologies was held at Zhejiang Univeristy in Hangzhou, China during May 18-20, 2018. It contains its workshop 2018 2nd International Conference on Business Information Systems (ICBIS 2018).

Presenter: Edgars Rencis, Institute of Mathematics and Computer Science, University of Latvia

Predicting Pregnant Shoppers Based On Purchase History Using Deep Convolutional Neural Networks

Presenter: Bibek Behera, Sears Holdings Corporation, India

Keynote Speakers of ICBDT 2018

Prof. Chen Wei, Zhejiang University, China

Dr. Wei Chen is a professor in State Key Lab of CAD&CG at Zhejiang University, P.R.China. From June 2000 to June 2002, he was a joint Ph.D student in Fraunhofer Institute for Graphics, Darmstadt, Germany and received his Ph.D degree in July 2002. His Ph.D advisors were Prof.Qunsheng Peng, and Prof.Georgios Sakas. From July. 2006 to Sep. 2008, Dr. Wei Chen was a visiting scholar at Purdue University, working in PURPL with Prof.David S. Ebert. In December 2009, Dr.Wei Chen was promoted as a full professor of Zhejiang University. He has performed research in visualization and visual analysis and published more than 30 IEEE/ACM Transactions and IEEE VIS papers. His current research interests include visualization, visual analytics and bio-medical image computing.

Speech Title: Visual analysis for big data
Abstract: In this presentation, I will briefly introduce the role of visual analysis for big data. I will explain how visual analysis benefits AI in an interactive way, and its influence on the future of AI. Examples from my research team will be demonstrated during the presentation.

Prof. Qigang Gao, Dalhousie University, Canada

Dr. Qigang Gao is a professor of Computer Science at Dalhousie University, Canada. He received both PhD and MASc degrees from the University of Waterloo, Canada in 1993 and 1988 respectively. His research interests include Computer vision & Pattern recognition, Data mining and Data warehousing, Web-based intelligent information systems, and Cloud computing. He has supervised/co-supervised 52 graduate students at both PhD and Masters levels, and published (authored/co-authored) 110 peer-reviewed research papers & book articles in the related areas. He has also served on the organizing and technical program committees of many conferences, and served as reviewer as well. Speaker URL: https://web.cs.dal.ca/~qggao/Speech Title: Big Data Research Collaboration - A Platform Showcase: Deepsense - A Center for Analytics and Ocean EconomyAbstract: Ocean expertise abounds on Canada’s east coast. In Nova Scotia alone, ocean-related activity generates $5 billion in revenue and produces 60,000 jobs – 14 per cent of provincial employment. More than 10 per cent of all researchers in Atlantic Canada are focused on oceans. What is missing? - A platform for accelerating a high-volume of industry driven applied Ocean Analytics projects through better and more supported collaboration, and with the aim of driving economic impact, that bring together the core assets of our Ocean’s cluster. This talk will present a showcase on big data analytics via a research collaboration platform: Deepsense, which was formed by both university research groups and industry sections. Deepsense currently includes the following proponents. IORE (Institute for Ocean Research Enterprise): Building partnerships to take marine research and translate it into real economic opportunity via COVE (Centre for Ocean Ventures & Entrepreneurship). FCS (Faculty of Computer Science): Computing and big data expertise; execution of applied analytics projects by professors, postdocs, graduate students. IBM: Business and R&D expertise, technical know-how, hardware and software tools.

Abstract: This paper is purported (1) to study the continuance intention toward and use of social commerce on WeChat; (2) to discover if the continuance intention toward and use of social commerce on WeChat are determined by perceived playfulness, perceived personalization, perceived socialization, and perceived trustfulness; (3) to explore if user personality traits such as extraversion, agreeableness, conscientiousness, neuroticism, and openness moderate the continuance intention and use of social commerce on WeChat. Study of this nature should contribute to the literature of social commerce, help discover critical social commerce strategies for WeChat, and help sustain stable user growth and the market share for WeChat.